CN108596111A - Safety cap recognition methods and device - Google Patents
Safety cap recognition methods and device Download PDFInfo
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- CN108596111A CN108596111A CN201810389588.2A CN201810389588A CN108596111A CN 108596111 A CN108596111 A CN 108596111A CN 201810389588 A CN201810389588 A CN 201810389588A CN 108596111 A CN108596111 A CN 108596111A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/40—Scenes; Scene-specific elements in video content
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Abstract
Safety cap recognition methods proposed by the present invention and device, by the real time video data for obtaining construction site；Then the real time video data is carried out taking stream, obtains unit stream video data；Then per unit stream video data are directed to, recognize whether the human body of the non-safe wearing cap in head；When to be, it is sent to client after current video flow data is preserved, so that supervisor corresponding with client can inform the timely safe wearing cap of the staff of non-safe wearing cap, to ensure life security.
Description
Technical field
The present invention relates to image processing fields, in particular to a kind of safety cap recognition methods and device.
Background technology
At present in construction field, usually safe wearing cap does not cause construction safety to ask to construction personnel due to itself
Topic.And it is typically to go to supervise by the teams and groups that construct for construction personnel's safe wearing cap, there are many objective factors, if supervision
Not in time, it is most likely that very serious safety accident problem can occur.
Invention content
In view of this, the embodiment of the present invention is designed to provide a kind of safety cap recognition methods and device, to alleviate
The above problem.
In a first aspect, an embodiment of the present invention provides a kind of safety cap recognition methods, the method is applied to server, institute
The method of stating includes：Obtain the real time video data of construction site；The real time video data is carried out to take stream, unit stream is obtained and regards
Frequency evidence；For per unit stream video data, the human body of the non-safe wearing cap in head is recognized whether；It, will when to be
Current video flow data is sent to client after preserving.
In conjunction with a kind of embodiment of first aspect present invention, the server includes RTMPS servers and identification clothes
Business device, it is described that the real time video data is carried out to take stream, unit stream video data are obtained, including：
The real time video data got is divided into multiple unit stream video data by the RTMPS servers,
In, each unit stream video data include one-frame video data；The real time video data is sent to as unit of frame
The identification server.
It is described to be directed to per unit stream video data in conjunction with a kind of embodiment of first aspect present invention, identify whether
There are the human bodies of the non-safe wearing cap in head, including：The identification server is based on pre-stored tensorflow depth
It practises algorithm and recognizes whether the human body of the non-safe wearing cap in head for per unit stream video data.
It is described to be directed to per unit stream video data in conjunction with a kind of embodiment of first aspect present invention, identify whether
There are the human bodies of the non-safe wearing cap in head, including：For per unit stream video data, the identification server identifies whether
There are human bodies；When to be, the head zone of each human body is obtained, recognizes whether the human body of the non-safe wearing cap in head
Head zone.
In conjunction with a kind of embodiment of first aspect present invention, the real time video data for obtaining construction site, including：
Obtain the real time video data that the camera of the tunnel inlet port of installation at the construction field (site) is sent.
Second aspect, an embodiment of the present invention provides a kind of safety cap identification device, described device is applied to server, institute
Stating device includes：Acquisition module, diverter module identify judgment module and judge execution module.Acquisition module is applied for obtaining
The real time video data at work scene；Diverter module takes stream for being carried out to the real time video data, obtains unit stream video number
According to；It identifies judgment module, for being directed to per unit stream video data, recognizes whether the people of the non-safe wearing cap in head
Body；Execution module is judged, for when the identification judgment module is judged as YES, being sent to after current video flow data is preserved
Client.
In conjunction with a kind of embodiment of second aspect of the present invention, the server includes RTMPS servers and identification clothes
Business device, the diverter module, including：Segmentation submodule in the RTMPS servers and sending submodule are set, it is described
Divide submodule, for the real time video data got to be divided into multiple unit stream video data, wherein Mei Yisuo
It includes one-frame video data to state unit stream video data；The sending submodule, for being with frame by the real time video data
Unit is sent to the identification server.
In conjunction with a kind of embodiment of second aspect of the present invention, the identification judgment module is arranged in the identification server
It is interior, for identifying whether to deposit for per unit stream video data based on pre-stored tensorflow deep learnings algorithm
In the human body of the non-safe wearing cap in head.
In conjunction with a kind of embodiment of second aspect of the present invention, the identification judgment module, for being directed to per unit stream
Video data recognizes whether human body；When to be, the head zone of each human body is obtained, recognizes whether head not
The head zone of the human body of safe wearing cap.
In conjunction with a kind of embodiment of second aspect of the present invention, the acquisition module, for obtaining installation at the construction field (site)
Tunnel inlet port camera send real time video data.
Compared with prior art, the advantageous effect for the safety cap recognition methods and device that various embodiments of the present invention propose
It is：By the real time video data for obtaining construction site；Then the real time video data is carried out taking stream, obtains unit stream and regards
Then frequency evidence is directed to per unit stream video data, recognizes whether the human body of the non-safe wearing cap in head；It is being yes
When, it is sent to client after current video flow data is preserved, so that supervisor corresponding with client can inform and not wear
The timely safe wearing cap of staff to wear a safety helmet, to ensure life security.
To enable the above objects, features and advantages of the present invention to be clearer and more comprehensible, preferred embodiment cited below particularly, and coordinate
Appended attached drawing, is described in detail below.
Description of the drawings
In order to illustrate the technical solution of the embodiments of the present invention more clearly, below will be to needed in the embodiment attached
Figure is briefly described, it should be understood that the following drawings illustrates only certain embodiments of the present invention, therefore is not construed as pair
The restriction of range for those of ordinary skill in the art without creative efforts, can also be according to this
A little attached drawings obtain other relevant attached drawings.
Fig. 1 is the schematic diagram that server provided in an embodiment of the present invention is interacted with client；
Fig. 2 is the structure diagram of server provided in an embodiment of the present invention；
Fig. 3 is the flow chart for the safety cap recognition methods that first embodiment of the invention provides；
Fig. 4 is the structure diagram for the safety cap identification device that second embodiment of the invention provides.
Specific implementation mode
Below in conjunction with attached drawing in the embodiment of the present invention, technical solution in the embodiment of the present invention carries out clear, complete
Ground describes, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.Usually exist
The component of the embodiment of the present invention described and illustrated in attached drawing can be arranged and be designed with a variety of different configurations herein.Cause
This, the detailed description of the embodiment of the present invention to providing in the accompanying drawings is not intended to limit claimed invention below
Range, but it is merely representative of the selected embodiment of the present invention.Based on the embodiment of the present invention, those skilled in the art are not doing
The every other embodiment obtained under the premise of going out creative work, shall fall within the protection scope of the present invention.
It should be noted that：Similar label and letter indicate similar terms in following attached drawing, therefore, once a certain Xiang Yi
It is defined, then it further need not be defined and explained in subsequent attached drawing in a attached drawing.Meanwhile the present invention's
In description, term " first ", " second " etc. are only used for distinguishing description, are not understood to indicate or imply relative importance.
As shown in Figure 1, being the schematic diagram that user terminal 100 provided in an embodiment of the present invention is interacted with server 200.
The server 200 is communicatively coupled by network 300 and one or more user terminals 100, with into row data communication or
Interaction.The server 200 may include network server, database server, RTMPS servers etc..Wherein, described
RTMPS server memories store up RTMPS.The user terminal 100 can be PC (personal computer, PC), put down
Plate computer, smart mobile phone, personal digital assistant (personal digital assistant, PDA) etc., inside preserve and take
Business device establishes the client of communication connection.
As shown in Fig. 2, being the block diagram of the server 200.The server 200 includes：Safety cap identification dress
Set, memory 110, storage control 120, processor 130, Peripheral Interface 140, input-output unit 150, audio unit 160,
Display unit 170.
The memory 110, storage control 120, processor 130, Peripheral Interface 140, input-output unit 150, sound
Frequency unit 160 and 170 each element of display unit are directly or indirectly electrically connected between each other, with realize data transmission or
Interaction.It is electrically connected for example, these elements can be realized between each other by one or more communication bus or signal wire.The peace
Full cap identification device include it is at least one can be stored in the memory 110 in the form of software or firmware (firmware) or
The software function module being solidificated in the operating system (operating system, OS) of client device.The processor 130
For executing the executable module stored in memory 110, such as the software function module that the safety cap identification device includes
Or computer program.
Wherein, memory 110 may be, but not limited to, random access memory (Random Access Memory,
RAM), read-only memory (Read Only Memory, ROM), programmable read only memory (Programmable Read-Only
Memory, PROM), erasable read-only memory (Erasable Programmable Read-Only Memory, EPROM),
Electricallyerasable ROM (EEROM) (Electric Erasable Programmable Read-Only Memory, EEPROM) etc..
Wherein, memory 110 is for storing program, and the processor 130 executes described program after receiving and executing instruction, aforementioned
Method performed by the server for the flow definition that any embodiment of the embodiment of the present invention discloses can be applied to processor 130
In, or realized by processor 130.
Processor 130 may be a kind of IC chip, the processing capacity with signal.Above-mentioned processor 130 can
To be general processor, including central processing unit (Central Processing Unit, abbreviation CPU), network processing unit
(Network Processor, abbreviation NP) etc.；Can also be digital signal processor (DSP), application-specific integrated circuit (ASIC),
Field programmable gate array (FPGA) either other programmable logic device, discrete gate or transistor logic, discrete hard
Part component.It may be implemented or execute disclosed each method, step and the logic diagram in the embodiment of the present invention.General processor
Can be microprocessor or the processor can also be any conventional processor etc..
The Peripheral Interface 140 couples various input/output devices to processor 130 and memory 110.At some
In embodiment, Peripheral Interface 140, processor 130 and storage control 120 can be realized in one single chip.Other one
In a little examples, they can be realized by independent chip respectively.
The interaction that input-output unit 150 is used to that user input data to be supplied to realize user and user terminal 100.It is described
Input-output unit 150 may be, but not limited to, mouse and keyboard etc..
Audio unit 160 provides a user audio interface, may include that one or more microphones, one or more raises
Sound device and voicefrequency circuit.
Display unit 170 provides an interactive interface (such as user interface) between user terminal 100 and user
Or it is referred to user for display image data.In the present embodiment, the display unit 170 can be liquid crystal display or touch
Control display.Can be that the capacitance type touch control screen or resistance-type of single-point and multi-point touch operation is supported to touch if touch control display
Control screen etc..Single-point and multi-point touch operation is supported to refer to touch control display and can sense on the touch control display one or more
The touch control operation generated simultaneously at a position, and transfer to processor 130 to be calculated and handled the touch control operation that this is sensed.
First embodiment
Fig. 3 is please referred to, Fig. 3 is a kind of flow chart for safety cap recognition methods that first embodiment of the invention provides, described
Method is applied to server.Flow shown in Fig. 3 will be described in detail below, the method includes：
Step S110：Obtain the real time video data of construction site.
As an implementation, camera can be installed at the inlet port of construction tunnel, camera for obtain into
Enter the real time video data of the personnel to construct in tunnel.Certainly, the camera is communicatively coupled with server.
After real-time video data is sent to server by camera, server can get real time video data.
Step S120：The real time video data is carried out to take stream, obtains unit stream video data.
Wherein, the server may include RTMPS servers and identification server.
RTMP is prestored in RTMPS servers.RTMP is Real Time Messaging Protocol (real-time messages
Transport protocol) acronym.
The real time video data got is divided into multiple unit stream video data by the RTMPS servers,
In, each unit stream video data may include one-frame video data, can also include multi-frame video data.Preferably,
In the present embodiment, preferred unit stream video data are one-frame video data.
RTMPS servers are sent to the identification server after shunting, by the real time video data as unit of frame.
Tensorflow deep learning algorithms are prestored in identification server, neural network learning can be first passed through in advance,
The classifications such as head and safety cap to identify human body, human body.
Step S130：For per unit stream video data, the human body of the non-safe wearing cap in head is recognized whether.
The identification server is based on pre-stored tensorflow deep learnings algorithm, can be directed to per unit stream
Video data recognizes whether the human body of the non-safe wearing cap in head.
Further, the identification server can be directed to per one-frame video data, and identification is in the frame video data
It is no that there are human bodies.
When to be, the identification server obtains the head zone of each human body again, recognizes whether that head is not worn
The head zone of the human body to wear a safety helmet.
Step S140：When to be, client is sent to after current video flow data is preserved.
Further, the identification server can there are the header areas of the human body of the non-safe wearing cap in head recognizing
When domain, send out red display, in the absence of, send out green display.
For client after getting current video flow data, supervisor corresponding with client, which can inform, does not wear peace
The timely safe wearing cap of staff of full cap, to ensure life security.
A kind of safety cap recognition methods that first embodiment of the invention provides, by the real-time video number for obtaining construction site
According to；Then the real time video data is carried out taking stream, obtains unit stream video data；Then it is directed to per unit stream video number
According to recognizing whether the human body of the non-safe wearing cap in head；When to be, visitor is sent to after current video flow data is preserved
Family end, so that supervisor corresponding with client can inform the timely safe wearing cap of the staff of non-safe wearing cap,
To ensure life security.
Second embodiment
Fig. 4 is please referred to, Fig. 4 is a kind of structure diagram for safety cap identification device 400 that second embodiment of the invention provides.
Described device is applied to server, and the server includes RTMPS servers and identification server.It below will be to shown in Fig. 4
Structure diagram be illustrated, shown device includes：
Acquisition module 410, the real time video data for obtaining construction site；
Diverter module 420 takes stream for being carried out to the real time video data, obtains unit stream video data；
It identifies judgment module 430, for being directed to per unit stream video data, recognizes whether the non-safe wearing in head
The human body of cap；
Execution module 440 is judged, for when the identification judgment module 430 is judged as YES, by current video flow data
Client is sent to after preservation.
As an implementation, the diverter module, including：Segmentation submodule in the RTMPS servers is set
Block and sending submodule；
The segmentation submodule, for the real time video data got to be divided into multiple unit stream video numbers
According to, wherein each unit stream video data include one-frame video data；
The sending submodule, for the real time video data to be sent to the identification server as unit of frame.
As an implementation, the identification judgment module is arranged in the identification server, for based on advance
The tensorflow deep learning algorithms of storage recognize whether that peace is not worn on head for per unit stream video data
The human body of full cap.
As an implementation, the identification judgment module identifies whether for being directed to per unit stream video data
There are human bodies；When to be, the head zone of each human body is obtained, recognizes whether the human body of the non-safe wearing cap in head
Head zone.
As an implementation, the acquisition module, for obtaining taking the photograph for the tunnel inlet port of installation at the construction field (site)
The real time video data sent as hair.
The present embodiment refers to above-mentioned the process of the respective function of each Implement of Function Module of safety cap identification device 400
Content described in Fig. 1 to embodiment illustrated in fig. 3, details are not described herein again.
In conclusion safety cap recognition methods and the device of proposition of the embodiment of the present invention, pass through and obtain construction site
Real time video data；Then the real time video data is carried out taking stream, obtains unit stream video data；Then it is directed to each list
Bit stream video data recognize whether the human body of the non-safe wearing cap in head；When to be, current video flow data is preserved
After be sent to client so that supervisor corresponding with client can inform that the staff of non-safe wearing cap wears in time
It wears a safety helmet, to ensure life security.
In several embodiments provided herein, it should be understood that disclosed device and method can also pass through
Other modes are realized.The apparatus embodiments described above are merely exemplary, for example, the flow chart in attached drawing and block diagram
Show the device of multiple embodiments according to the present invention, the architectural framework in the cards of method and computer program product,
Function and operation.In this regard, each box in flowchart or block diagram can represent the one of a module, section or code
Part, a part for the module, section or code, which includes that one or more is for implementing the specified logical function, to be held
Row instruction.It should also be noted that at some as in the realization method replaced, the function of being marked in box can also be to be different from
The sequence marked in attached drawing occurs.For example, two continuous boxes can essentially be basically executed in parallel, they are sometimes
It can execute in the opposite order, this is depended on the functions involved.It is also noted that every in block diagram and or flow chart
The combination of box in a box and block diagram and or flow chart can use function or the dedicated base of action as defined in executing
It realizes, or can be realized using a combination of dedicated hardware and computer instructions in the system of hardware.
In addition, each function module in each embodiment of the present invention can integrate to form an independent portion
Point, can also be modules individualism, can also two or more modules be integrated to form an independent part.
It, can be with if the function is realized and when sold or used as an independent product in the form of software function module
It is stored in a computer read/write memory medium.Based on this understanding, technical scheme of the present invention is substantially in other words
The part of the part that contributes to existing technology or the technical solution can be expressed in the form of software products, the meter
Calculation machine software product is stored in a storage medium, including some instructions are used so that a computer equipment (can be
People's computer, server or network equipment etc.) it performs all or part of the steps of the method described in the various embodiments of the present invention.
And storage medium above-mentioned includes：USB flash disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), arbitrary access are deposited
The various media that can store program code such as reservoir (RAM, Random Access Memory), magnetic disc or CD.It needs
Illustrate, herein, relational terms such as first and second and the like be used merely to by an entity or operation with
Another entity or operation distinguish, and without necessarily requiring or implying between these entities or operation, there are any this realities
The relationship or sequence on border.Moreover, the terms "include", "comprise" or its any other variant are intended to the packet of nonexcludability
Contain, so that the process, method, article or equipment including a series of elements includes not only those elements, but also includes
Other elements that are not explicitly listed, or further include for elements inherent to such a process, method, article, or device.
In the absence of more restrictions, the element limited by sentence "including a ...", it is not excluded that including the element
Process, method, article or equipment in there is also other identical elements.
The foregoing is only a preferred embodiment of the present invention, is not intended to restrict the invention, for the skill of this field
For art personnel, the invention may be variously modified and varied.All within the spirits and principles of the present invention, any made by repair
Change, equivalent replacement, improvement etc., should all be included in the protection scope of the present invention.It should be noted that：Similar label and letter exist
Similar terms are indicated in following attached drawing, therefore, once being defined in a certain Xiang Yi attached drawing, are then not required in subsequent attached drawing
It is further defined and is explained.
The above description is merely a specific embodiment, but scope of protection of the present invention is not limited thereto, any
Those familiar with the art in the technical scope disclosed by the present invention, can easily think of the change or the replacement, and should all contain
Lid is within protection scope of the present invention.Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. a kind of safety cap recognition methods, which is characterized in that the method is applied to server, the method includes：
Obtain the real time video data of construction site；
The real time video data is carried out to take stream, obtains unit stream video data；
For per unit stream video data, the human body of the non-safe wearing cap in head is recognized whether；
When to be, client is sent to after current video flow data is preserved.
2. according to the method described in claim 1, it is characterized in that, the server includes RTMPS servers and identification clothes
Business device, it is described that the real time video data is carried out to take stream, unit stream video data are obtained, including：
The real time video data got is divided into multiple unit stream video data by the RTMPS servers, wherein every
The one unit stream video data include one-frame video data；
The real time video data is sent to the identification server as unit of frame.
3. according to the method described in claim 2, it is characterized in that, it is described be directed to per unit stream video data, identify whether
There are the human bodies of the non-safe wearing cap in head, including：
The identification server is based on pre-stored tensorflow deep learnings algorithm, for per unit stream video number
According to recognizing whether the human body of the non-safe wearing cap in head.
4. according to the method described in claim 3, it is characterized in that, it is described be directed to per unit stream video data, identify whether
There are the human bodies of the non-safe wearing cap in head, including：
For per unit stream video data, the identification server recognizes whether human body；
When to be, the head zone of each human body is obtained, recognizes whether the head of the human body of the non-safe wearing cap in head
Region.
5. according to the method described in claim 4, it is characterized in that, it is described obtain construction site real time video data, including：
Obtain the real time video data that the camera of the tunnel inlet port of installation at the construction field (site) is sent.
6. a kind of safety cap identification device, which is characterized in that described device is applied to server, and described device includes：
Acquisition module, the real time video data for obtaining construction site；
Diverter module takes stream for being carried out to the real time video data, obtains unit stream video data；
It identifies judgment module, for being directed to per unit stream video data, recognizes whether the people of the non-safe wearing cap in head
Body；
Execution module is judged, for when the identification judgment module is judged as YES, being sent after current video flow data is preserved
To client.
7. device according to claim 6, which is characterized in that the server includes RTMPS servers and identification clothes
Business device, the diverter module, including：Segmentation submodule in the RTMPS servers and sending submodule are set,
The segmentation submodule, for the real time video data got to be divided into multiple unit stream video data,
In, each unit stream video data include one-frame video data；
The sending submodule, for the real time video data to be sent to the identification server as unit of frame.
8. device according to claim 7, which is characterized in that the identification judgment module is arranged in the identification server
It is interior, for identifying whether to deposit for per unit stream video data based on pre-stored tensorflow deep learnings algorithm
In the human body of the non-safe wearing cap in head.
9. device according to claim 8, which is characterized in that the identification judgment module, for being directed to per unit stream
Video data recognizes whether human body；When to be, the head zone of each human body is obtained, recognizes whether head not
The head zone of the human body of safe wearing cap.
10. device according to claim 9, which is characterized in that the acquisition module, for obtaining installation at the construction field (site)
Tunnel inlet port camera send real time video data.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810389588.2A CN108596111A (en) | 2018-04-26 | 2018-04-26 | Safety cap recognition methods and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810389588.2A CN108596111A (en) | 2018-04-26 | 2018-04-26 | Safety cap recognition methods and device |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN108596111A true CN108596111A (en) | 2018-09-28 |
Family
ID=63610072
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810389588.2A Pending CN108596111A (en) | 2018-04-26 | 2018-04-26 | Safety cap recognition methods and device |
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| CN (1) | CN108596111A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109376676A (en) * | 2018-11-01 | 2019-02-22 | 哈尔滨工业大学 | Highway engineering site operation personnel safety method for early warning based on unmanned aerial vehicle platform |
| CN111259855A (en) * | 2020-02-09 | 2020-06-09 | 天津博宜特科技有限公司 | Mobile safety helmet wearing detection method based on deep learning |
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| KR20120038640A (en) * | 2010-10-14 | 2012-04-24 | 대우조선해양 주식회사 | Safty system of heavy weight moving apparatus using image processing |
| CN104902227A (en) * | 2015-05-06 | 2015-09-09 | 南京第五十五所技术开发有限公司 | Substation helmet wearing condition video monitoring system |
| CN106372662A (en) * | 2016-08-30 | 2017-02-01 | 腾讯科技（深圳）有限公司 | Helmet wearing detection method and device, camera, and server |
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Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| KR20120038640A (en) * | 2010-10-14 | 2012-04-24 | 대우조선해양 주식회사 | Safty system of heavy weight moving apparatus using image processing |
| CN104902227A (en) * | 2015-05-06 | 2015-09-09 | 南京第五十五所技术开发有限公司 | Substation helmet wearing condition video monitoring system |
| CN106372662A (en) * | 2016-08-30 | 2017-02-01 | 腾讯科技（深圳）有限公司 | Helmet wearing detection method and device, camera, and server |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109376676A (en) * | 2018-11-01 | 2019-02-22 | 哈尔滨工业大学 | Highway engineering site operation personnel safety method for early warning based on unmanned aerial vehicle platform |
| CN111259855A (en) * | 2020-02-09 | 2020-06-09 | 天津博宜特科技有限公司 | Mobile safety helmet wearing detection method based on deep learning |
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